Affiliations: [a] School of Computer and Information Science, Hubei Engineering University, Xiaogan, Hubei, China | [b] Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, Hubei, China
Correspondence:
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Corresponding author: Fang Xu, School of Computer and Information Science, Hubei Engineering University, Xiaogan, Hubei, China. E-mail: :xf@hbeu.edu.cn.
Abstract: In the social internet of things, community structure exists objectively and affects the transmission of network messages. If the social context such as community is fully utilized, the efficiency of data forwarding will be effectively improved. A community-based routing algorithm (MSAR) is proposed by studying the multiple social relationships. First, we propose four measures of social relationships. They are social closeness degree, in-community activeness, cross-community activeness and community interaction. Then, the design of routing algorithm considers two stages. One is in-community forwarding and the other is cross-community forwarding. The measurement of node forwarding capability depends on closeness degree and in-community activeness in the in-community forwarding stage. In the cross-community stage, the measurement of node forwarding capability depends on closeness degree, cross-community activeness and community interaction. The relay node with higher cross-community forwarding utility will be selected. This prevents messages from being limited to the local community. Therefore, messages can always travel in the direction of the destination node’s community. Finally, a lot of simulation experiments and analyses are carried out. The analysis results show that the proposed algorithm has good performance in the following two aspects, the average latency and the message delivery rate respectively.
Keywords: Social Internet of Things, routing, closeness, activeness, community interaction
